A global model of hourly space heating and cooling demand at multiple spatial scales
A global model of hourly space heating and cooling demand at multiple spatial scales
复制标题
多个空间尺度上每小时空间供暖和制冷需求的全球模型
DOI：
10.1038/s41560-023-01341-5
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发表时间：
2023
期刊：
影响因子：
56.7
通讯作者：
Staffell I
中科院分区：
文献类型：
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作者：
Staffell I
准确模拟天气对建筑能源需求的时间和空间影响对于能源系统脱碳至关重要。在这里，我们介绍了适用于全球所有空间尺度的每小时供暖和制冷需求的可定制模型。我们根据四大洲 43 个地区约 5,000 座建筑的需求进行验证。该模型需要有限的数据输入，并且比现有模型更符合测量需求。我们首先用它来证明，所有建筑物的恒温器设置降低 1°C 可以将欧洲的天然气消耗量减少 240TWh yr−1，大约是历史上从俄罗斯进口的六分之一。其次，我们发现，由于气候变化，某些地区的制冷服务需求每年增加高达 5%，与上一代人相比，每年有 50 亿人经历超过 100 度的制冷天数。该模型和基础数据可免费访问，以促进进一步的研究。
Accurate modelling of the weather’s temporal and spatial impacts on building energy demand is critical to decarbonizing energy systems. Here we introduce a customizable model for hourly heating and cooling demand applicable globally at all spatial scales. We validate against demand from ~5,000 buildings and 43 regions across four continents. The model requires limited data inputs and shows better agreement with measured demand than existing models. We use it first to demonstrate that a 1 °C reduction in thermostat settings across all buildings could reduce Europe’s gas consumption by 240 TWh yr−1, approximately one-sixth of historical imports from Russia. Second, we show that service demand for cooling is increasing by up to 5% per year in some regions due to climate change, and 5 billion people experience >100 additional cooling degree days per year when compared with a generation ago. The model and underlying data are freely accessible to promote further research.